Methods, software, and systems for over-the-counter trading

ABSTRACT

Methods, software, and hardware are disclosed for providing verified real time price quotes in an over-the-counter financial market. Systems are described that can comprise methods, software, and/or hardware to provide verified real time price information for securities traded over-the-counter. Verification methods of the invention include identifying suspect source data, wherein the suspect source data includes information about the price of a security, verifying the suspect source data, and displaying to a user a verified price quote of a security traded in an over-the-counter market to a user. The verification methods of the invention include using hash functions and hash tables to process suspect source data, wherein the hashing allows for confidential processing while at the same time maintaining the ability to match a price quote to the source of the price quote.

FIELD OF THE INVENTION

The present invention relates to methods, software, and systems forgenerating verified price quotes in a financial market, including in anover-the-counter securities market. The invention also relates tomethods of identifying suspect data wherein the suspect data comprises aprice quote for a security in a financial market. The inventioncomprises methods, software, and systems for verifying financialinformation, such as price quotes, from one or more sources, includingtransmitting suspect data electronically in encrypted form, anddisplaying verification status of the suspect data. The inventioncomprises using hash functions in analyzing price quote data in afinancial market.

BACKGROUND

Unlike equities, many financial asset classes do not trade on anelectronic exchange with real-time price discovery and execution, butinstead trade in what is referred to as an “over-the-counter” (OTC)market.

Participants in these over-the-counter markets source pricing levels andexecute trades primarily via email, telephone and broker websites. Asyoung markets develop and more assets begin trading, the volume of datareceived—particularly via email—rapidly becomes too large to beefficiently assimilated. In order for traders to discover the bestprices, and with whom they should execute the trade, traders must scourthrough their email inboxes and numerous websites to find the bestquotes.

Every day, traders receive huge volumes of pricing data in heterogeneousformats via different media. Without a system for handling that data,much—if not all of it—is effectively useless. Methods, software, andsystems by which traders in certain over-the-counter derivatives canidentify, organize and store, in real time, heterogeneous pricing datareceived via email or the web from dealers, would facilitate moreefficient trading. Accordingly, methods, software, and systems fordetermining best prices and trading partners are needed for efficienttrading in over-the-counter markets.

SUMMARY OF INVENTION

Methods, software, and systems are disclosed for providing real-timesource data information in over-the-counter financial markets. Variousembodiments are disclosed wherein the methods, software, and systemsdescribed herein manipulate source data to achieve presentation ofpricing information in real time for traders in over-the-countermarkets. Presentation of pricing information in real time includesimmediate capture and display of structured data captured fromstructured and unstructured data sources, as opposed to delayedstructuring and display of data that would, for example, result frommanual data entry.

The invention comprises methods for providing a price quote on asecurity traded in an over-the-counter financial market, comprising:receiving source data comprising price information of the security;storing the source data on a computer readable medium; processing thesource data using a computer processor, wherein the processing comprisesextracting a price quote from the source data for the security,comparing the price quote to at least one pre-selected criterion, andstoring the compared price quote on a computer readable medium; and,transmitting the compared price quote. The compared price can betransmitted to system users, such as, for example, traders and riskmanagers, and in the case of exception data, data editors for manualvalidation.

The methods comprise embodiments wherein the source data is receivedfrom multiple sources and wherein the source data comprises more thanone price quote for the security.

In various embodiments, the source data received from at least a firstsource and a second source, wherein the source data received from thefirst source is in a different format than the source data received fromthe second source. Various formats of the source data include thosecomprising an email, html, text, xml, or combinations thereof.

Various embodiments include processing the source data by parsing thesource data before comparing the source data to the pre-selectedcriterion (or criteria). The parsing may comprise categorizing words,patterns, and/or numbers in the data source to identify market data orthe price quote in the source data.

Methods of the invention are also provided that comprise designatingsource data that does not meet the criterion (or criteria) as suspectdata.

The invention also comprises methods, software, and systems forgenerating verified price quotes for securities traded in anover-the-counter financial market, comprising: receiving source datacomprising information about the price of a security; storing the sourcedata on a computer readable medium; processing the source data using acomputer processor, wherein the processing comprises identifying suspectsource data, assigning a hash key to suspect source data, wherein thehash key comprises a price quote and the identity of the data source;verifying the suspect source data using the hash key, and converting thehash key into a verified price quote. In various embodiments, the hashkey can be encrypted.

The invention also comprises a method for computing VaR, comprisingemploying the methods of the invention to generate real time pricequotes, including verified price quotes, and using the real time pricequotes in a VaR method. Any suitable VaR model or algorithm can be usedin connection with the invention. In some embodiments, the inventioncomprises employing the methods of the invention to generate verifiedprice quotes and using the verified price quotes to compute a VaR for aportfolio, wherein the VaR is employed to set trading limits on thesecurities comprising the portfolio.

For a better understanding of the present invention together with otherand further advantages and embodiments, reference is made to thefollowing description taken in conjunction with the examples, the scopeof the which is set forth in the appended claims.

BRIEF DESCRIPTION OF THE FIGURES

The preferred embodiments of the invention have been chosen for purposesof illustration and description but are not intended to restrict thescope of the invention in any way. The preferred embodiments of certainaspects of the invention are shown in the accompanying figure, wherein:

FIG. 1 illustrates market data flow in an investment bank, comprising averification process for suspect price quotes employing a centraldatabase for verifying suspect quotes.

FIG. 2 illustrates an embodiment of the invention comprising a clientarchitecture for handling source data.

FIG. 3 illustrates an embodiment of the invention comprising employing asingle central parser processing data from a number of clients.

FIG. 4 illustrates an embodiment of the invention wherein each usershares system maintenance, and updates are shared between peers.

FIG. 5. illustrates an embodiment of the invention comprising employinga system employed by originators of market data, wherein the system isemployed to either preformat email or use email to create quotes fordistribution to clients.

FIG. 6 illustrates an embodiment of the invention comprising a parserlocated within a common communication/messaging network such that quotesare distributed with, or instead of, original text from source data.

FIG. 7 illustrates an embodiment of the invention for markets where nocentral maintenance and verification are needed, and is maintainedinstead by clients and through periodic software updates.

FIG. 8 illustrates a process of the invention wherein source data, whichcan comprise data in any format, is stored on a computer readable medium(CRM), processed by, for example, parsing, then stored again, andcompared to at least one pre-selected criterion.

FIG. 9 illustrates one embodiment wherein verification is achievedthrough transmission of hashed suspect source data.

FIG. 10 illustrates one embodiment of the invention that shows howhashing can be used in at least one embodiment in generating verifiedprice quotes on an over-the-counter security.

FIG. 11 illustrates one embodiment using an encrypted hash key togenerate verified price quotes on an over-the-counter security.

DETAILED DESCRIPTION OF INVENTION

The present invention will now be described in connection with preferredembodiments. These embodiments are presented to aid in an understandingof the present invention and are not intended to, and should not beconstrued, to limit the invention in any way. All alternatives,modifications and equivalents that may become obvious to those ofordinary skill upon reading the disclosure are included within the spritand scope of the present invention.

This disclosure is not a primer on computer software or hardware; basicconcepts known to those skilled in the art have not been set forth indetail.

One aspect of the present invention comprises a method for providing aprice quote on a security traded in an over-the-counter financialmarket, comprising: (a) receiving source data comprising priceinformation of the security; (b) storing the source data on a computerreadable medium; (c) processing the source data using a computerprocessor, wherein the processing comprises extracting a price quotefrom the source data, comparing the price quote to at least onepre-selected criterion, and storing the compared price quote on acomputer readable medium; and, (d) displaying the compared price quote,wherein the compared price quote comprises a price quote for a securitytraded in an over-the-counter financial market.

In another aspect, the invention comprises a method for generatingverified price quotes for securities traded in an over-the-countermarket, comprising: (a) receiving source data on a first computerreadable medium, wherein the source data comprises information about theprice of a security; (b) storing the source data on the computerreadable medium; (c) processing the source data, wherein the processingcomprises identifying suspect source data, assigning a hash key tosuspect source data, wherein the hash key comprises a price quote andthe identity of the data source; (d) verifying the suspect source datausing the hash key, and (e) displaying information about the verifiedsuspect source data to a user. In various embodiments, the hash key canbe encrypted.

A general description of a has function (H) is a transformation thattakes a variable size input (m) and returns a fixed-size string called ahash value h, such that h=H(m). Hash functions can be one-way. A one-wayhash function is selected such that it computationally infeasible tofind an input x such that H(x)=h. Applications of hash functions areknown to those of skill in the art, and include, for example, stringhashing, cryptographic hashing, geometric hashing, and Bloom filters.Many hash functions are known to those of skill in the art.

It is known in the art that data storage and identification can beachieved through associating a data packet, or collection of data, witha key. The key and the associated data can be associated such that thekey includes an address, or instructions on how to find, the data packetor collection of data associated with the key. In this context, the keyand the associated data can be described as an item, wherein the item isa packet—or collection, of data or information that comprises at least akey that identifies the item—and the remainder of the data comprisingthe item. Hashing is a technique that has been used for calculating astorage address for a stored data item from a data item's key. Hashinghas been used to convert an item's key into a random or near-randomnumber, which is then scaled to provide the storage address for theitem. The storage address is generally an address where groups of itemscan be stored. Generically, an item's key can be hashed to produce anidentifier that can comprise a random number designating a storageaddress (or bin), the physical location of the storage address isascertained (by, for example, searching a look-up table of storageaddresses), and the item is then stored at the storage address (or bin).Accessing the item can be achieved by hashing the item's key to producethe identifier, ascertaining the physical location of the storageaddress, and searching at the storage address for the item. The key istypically expressed numerically and a random or near-random number isgenerated that corresponds to the key using algorithms known in the art.

Hash tables can be used to store information used to classify receivedpackets into corresponding streams of data packets communicated(directly or indirectly) from a first node (for example, a source node)to a second node (for example, a destination node). Hash tablescomprise, in general, tables of linked lists. The lists can be indexedby applying a hash function to signature information, wherein signatureinformation comprises information that is constant with regard tocorresponding data packets. Signature information can be used to relate,or correspond, data packets according to one or more suitable criteria.

A common application of hash functions is in data retrieval. In thiscontext, data is stored on a computer readable medium such as, forexample, a hard drive. The data is physically located at a storageaddress that corresponds to a pointer to the storage address. Thepointer comprises an entry in a hash bucket, where the hash bucket cancomprise multiple pointers to multiple storage addresses. The bucket isassociated with a key; thus, all the pointers in the bucket areassociated with the key corresponding to that particular bucket. Thebucket is part of a hash table, wherein the hash table comprises aplurality of hash buckets. Each bucket has a corresponding hash key,wherein the key is generated by applying a hash function to thecorresponding stored data. Data thus stored can be retrieved from thestorage device by inputting a search term corresponding to the storeddata, applying the hash function to the search term to obtain the hashkey, locating the bucket comprising the key, identifying the pointer tothe stored data associated with the search term, locating the storageaddress of the stored data, and comparing the stored data to the searchterm.

The present invention comprises novel uses of hashing in providingverified price quotes in an over-the-counter securities market.

In embodiments employing parsing of source data, parsing can includecategorizing words, patterns, and/or numbers in the data source toidentify market data in the source data. The parsing can be donemanually—that is, by a human operator viewing the source data on acomputer display, parsing, and inputting the results of the parsing intocomputer readable form—or the parsing can be done in whole or in part bya computer processor employing an algorithm in the form of parsingsoftware. Suitable parsing software for identifying market data insource data includes PERL regular expressions.

The parsing can comprise parsing of quotes in any over-the-countermarket of interest, including, for example, convertible, bond, index,CDS, and tranche quotes, regardless of the source or format. In variousembodiments, the parser parses corporate and credit default indices.Nonlimiting examples of such indices include the Dow Jones NorthAmerican Investment Grade index—or DJ CDX NA IG index, the Dow JonesNorth American High Yield Index—or DJ CDX NA HY index, and iTraxxindices.

In various embodiments, the invention helps users and marketparticipants efficiently aggregate available data in real-time byparsing structured and unstructured emails and website text, andpopulating a database with the market quotes organized by tradablecontract, market maker, and bid and offer levels. Via any suitableadd-ins, such as, for example, a GUI and Excel add-in, users and marketparticipants can see for a given contract, a bid/offer stack of pricesshown to them by their counterparties. For example, at a single glance,a trader is able to see with which counterparty they can get bestexecution and at what level. Accordingly, traders in over-the-countermarkets can see all relevant market quotes shown to them in a singlescreen or display, leading to faster and better execution.

In various embodiments, the at least one criterion is a criterion thatidentifies suspect data. Suspect data comprises data that includesmarket prices that are outside an expected range of values and contractsof unusually short or unusually long tenor. Designating source data assuspect data can be achieved by a human operator, having viewed thesource data in computer readable form, and applying the criterion (orcriteria) to the source data and deciding, based on the criterion (orcriteria) whether the data is suspect or not. Where data is notdesignated as suspect, the price quote can be extracted from the dataand displayed to a user in, for example, a ranking of price quotesassociated with the identity of the originator of the price quote. Wheredata is designated as suspect, the source data is further examined todetermine whether it is indeed valid, or has been miscategorized (inwhich case it is recategorized).

In various embodiments, source data arrives at a single location,wherein the location comprises a system comprising at least one devicecapable of receiving the source data (such as, for example, an inputdevice), at least one processor, and a medium for storing computerreadable data. The method can be carried out at a single location.

In various embodiments, the method can be carried out at more than onelocation. In one nonlimiting example, the method can be carried out asfollows: A first system comprising at least one input device capable ofreceiving the source data, at least one processor, and at least onestorage medium, receives source data. The processor, according to atleast one pre-selected criterion, determines which source data comprisessuspect source data. Once identified, suspect source data is compiled bythe source data and stored. The stored suspect source data comprises atleast price information and the originator of the price information. Inthis context, the originator of the price information includes theaddress (e.g., one or more of email address, url, IP address, postaladdress, phone number, company name, etc.) of the entity or person wherethe price information appeared.

In various embodiments, the step of verifying the suspect source datausing the hash key comprises transmitting the suspect source data in thehash key to a verifier, wherein the verifier verifies the suspect sourcedata and transmits to a user a computer readable message comprising averification, a verification failure, or a combination thereof.

The suspect source data can be stored in a secure form. The secure formcan comprise, as described herein, a hash key or hash table thatcomprises information at least about the originator of a price quote andthe price quote itself. Suspect source data from more than one sourcecan be stored together. For example, identities of originators and theprice quotes from each originator can be saved together in a singlesecure form for transmission over a telecommunications line.

The telecommunications line can include a secure line or an insecureline. The transmission can be achieved on an insecure line without thelikelihood of revealing the identity of the originator and the pricequote being revealed, because the identity of the originator and theassociated price quote are encoded in a hash key or encrypted hash keyor hash table as described herein. Advantages of this embodiment includethe ability to compile, or mix, two or more price quotes associated withtwo or more originators into a single transmission. Only recipients thatare able to gain access to the information in the hash key or hash tablecan view the identity of the originator and the associated price quote.In various embodiments, the hash key and/or hash table can be encryptedemploying a suitable encryption method known in the art. Suitableencryption methods are described herein.

The invention comprises a computer-implemented system that facilitatesthe real time aggregation of structured and unstructured electronicmarket data sources for over-the-counter financial markets. Thisincludes a method and system by which new formats of source data can becategorized and processed. Using this system, source data can be madeanonymous and uniquely identifiable. The system can be built around acentralized hub, and users can submit their source data forcategorization, the resultant categorized source data being returned andstored locally at a client. Or the categorized source data can be storedat a location distant from a client and accessed remotely by a client.The systems of the invention can be maintained by a centraladministrator, peers (i.e., users), or a combination thereof. The systemcan also be maintained locally.

Embodiments of the invention include methods, software, and systems thatparse emails and websites for dealer quotes in certain over-the-counterderivatives. Such embodiments may include a data flow system (“Data FlowSystem”) for the cleaning of data identified as anomalous withoutbreaching copyrights and rights of confidentiality in the anomalous dataof the creator of the relevant data (e.g., email or website). Anomalousdata are identified on an exception basis and manually checked andcleaned, resulting in accurate and comprehensive output.

Advantages of the methods, software, and systems described hereininclude, for example, access to high quality, verified source data inreal time. The methods, software, and systems can, for example, storequotes in a local database, enable traders to access and analyze storedquotes by, for example, a graphical user interface or an add-in such as,for example, a Microsoft Excel add-in; allow traders to access quotestick-by-tick; allow traders to readily view ranked bids and offers;enable traders to determine best available prices for any given securityand the identity of the relevant dealer; enable traders to performcomplex analytics across a portfolio of securities; and enable tradersto more accurately mark-to-market their books.

Nonlimiting examples of over-the-counter markets for which the inventionis useful include the corporate bond market, the convertible bondmarket, the credit default swap market, the credit indexes market andthe index tranches market.

The methods, software, and systems described herein can be readilyadapted to a wide variety of over-the-counter markets or phenomena suchas, for example, high yield bonds, convertible bonds, equity volatility,etc. One application of the invention includes a price quote system fora credit default swap (CDS) market, where a typical trader receivesaround 1,500 emails a day, containing over 3,000 distinct market quotes.Real time ranked bids and offers allows users to analyze the depth ofthe market for each security and virtually instantly survey up-to-dateprice histories that can be used to compare current quotes with storedprice quotes. The exception-based cleaning embodiments of the inventionhelp ensure data integrity and reliability. Anomalous data is identifiedon an exception basis and manually checked and cleaned, resulting in anaccurate and comprehensive output. With the present invention, financialmarket participant such as, for example, traders, portfolio managers,and risk managers, can now enjoy a real-time price quote parsing toolthat includes the structuring of market pricing data that can enhancetrading performance and reduce costs.

Having been subject to comparison with one or more pre-selectedcriteria, the source data can be stored in a computer readable medium.Before or after storage, the compared source data can be categorized, orplaced in virtual bins, according to the comparison(s). The comparedsource data can be displayed in any suitable or desirable format forviewing by a user. One desirable format comprises a price quote in aranking of price quotes, wherein the originator of the price quote isidentified in conjunction with the price quote. In this way, a user canreadily inspect a display that comprises price quotes generated from avariety of source data, organized in a ranked display of increasing ordecreasing prices for a particular security, and the identity and/orcontact information for the originator of the price quote.

The method can further comprise the step of processing the source data,wherein the step comprises parsing the source data before, after, orduring comparing the source data to the at least one pre-selectedcriterion.

In various embodiments, the source data can be received from multiplesources, and the source data can comprise more than one price quote forthe security. The source data can be from multiple sources, and each thedata from the multiple sources need not be in the same format. Formatscan include, for example, email, html, text, xml, or combinationsthereof. For example, a data comprising an email can be received from afirst source, and data comprising html—or a web page or link—can bereceived from a second source. Both the email and the html data includea price quote for a security that is relevant in an over-the-countermarket. The multiple sources can number, for example, in the thousands.Each data source can comprise more than one price quote.

The invention can be practiced in a distributed computing environment ornetwork where processes can be carried out by processing devices thatare linked through, for example, a communications network. Distributedcomputing environments include computer networks. Distributed computingenvironments include environments where computer executable instructionscan be located in either or both local and remote computer storagemedia, including in computer readable media (CRM) such as, for example,memory storage devices. Memory storage devices include, for example,hard drives, suitable optical disks such as CD-ROMs, floppy disks, ROM(read only memory), PROM (programmable read only memory), RAM (randomaccess memory), EPROM (erasable programmable read only memory), EEPROM(electrically erasable programmable read only memory), flash EPROM(i.e., nonvolatile memory) memory cards, flash memory, or any othersuitable computer-readable media. The invention can be practiced usingany suitable hardware, software, firmware, or combination thereof.

Where a process can take place by way of a computer, the process can becarried out by any suitable executable instructions. Computer executableinstructions include routines, subroutines, computer programs, objects,data structures, and the like that perform certain functions ormanipulate or implement data types of interest.

The invention can be practiced with any suitable combination ofprocessing; input/output devices; display devices; and/orgeneral-purpose or special-purpose processors or logic circuitsprogrammed with the methods of the invention. Such devices can include,for example, personal computers, servers, client devices, personal dataassistants (PDAs), hand-held devices, laptops, programmable electronics,computer networks such as, for example, a personal computer (PCT)network, a mainframe, a miniframe, and a suitable distributed computingenvironments that includes any of the foregoing.

The computer readable medium can comprise any suitable computer readablemedium known in the art. For example, the computer readable medium cancomprise a mainframe or desktop computer, wherein the mainframe ordesktop comprises an input enabling the computer to receive the datasources. The mainframe or desktop further comprises software capable ofreceiving and storing the data sources. Suitable software capable ofreceiving and storing the data sources include MICROSOFT™ ExchangeServer and MICROSOFT SQL server.

The source data in computer readable form is processed using a computerprocessor. Suitable computer processors include INTEL® PENTIUM® 4 2.80GHz. Employing the suitable processor, a price quote is extracted fromthe source data. The extracting can be done manually, that is, by ahuman operator, or can be achieved employing a computer program toidentify and extract price data from the source data. A suitablecomputer program to identify and extract price data from the source dataincludes PERL regular expressions. Once the price data is extracted, itcan be stored and/or directly used to compare the price data to at leastone pre-selected criterion. The pre-selected criterion can include, forexample, most recent asset price bid and offer.

One feature of the invention is scalability, wherein the scalabilitystems from the observation that in a given market, there are actually avery small number of participants generating original email markets.Within a typical investment bank, there will normally only be one tradermaking a market on a given asset. This information is communicated byemail to a sales team who then, having perhaps added their own marketcommentary, forward the markets to their clients.

This market data flow is depicted in FIG. 1. This commonality gives riseto two important results: (1) the markets made by the original traderare received in the same format by most, if not all clients; and, (2)any systematic error, or bad data produced during the parsing process,is the same for all recipients, and by grouping suspect data together,is inspected or edited only once.

In one embodiment, the invention comprises four main components. Anonlimiting example of the arrangement of the components is depicted inFIG. 2. The first component is the parser which categorizes words,patterns and numbers in the incoming email or website text, and atpresent uses an expert system to capture the market data containedtherein. Other methods considered for the parser engine include neuralnetworks, a template based system (for structured text), Bayesiannetworks, natural language processing, and layered combinations of theprevious methods for increased yields from markets including bothstructured and unstructured source formats.

The components for all configurations can be the same, or similar.Differing configurations can be employed to select the most suitablelayout given prevailing solution scalability.

Once the text has been parsed, the captured market quotes are comparedwith an expectation level for the given asset, and if within range, areadded to the database and visible output as “clean” quotes. Quotesfalling outside the expected range are flagged for manual verification.These are either a result of valid large market movements or parsermisclassification.

Financial markets are always rapidly evolving both in terms of assettypes, entities on which the assets are traded and the quotingconventions and formats used. In order to keep abreast of these changes,static data needs to be continuously enhanced and parser definitionsneed to be updated. For each user to do this independently makes littlesense due to the duplication of effort involved and specialist knowledgeand skill set required. To satisfy these needs, the invention cancomprise incorporation of a centralized service that updates clientinstallations with up to date static data and parser definitions on adaily basis.

In order to satisfy legal requirements for the forwarding of suspectquotes to an external third party for verification, the source of thequotes has to be anonymous. However, in order to pool suspect quotes forverification, the source has to be included. The solution the inventionimplements is to create a hash key from a combination of the basic quoteinformation (bid, offer, entity, term etc) and source. This hash key canthen be encrypted using the MD5 algorithm to create a unique, anonymousidentifier. Suspect quotes then received centrally with the same hashkey are grouped and processed together as one quote.

In a similar fashion the associated body text of the source email orwebsite can be sent in its entirety along with a suspect quote to aidthe data verification process. In this instance, the parser stores downthe column and row coordinates of each match it makes that is not initself an actual quote level. These coordinates are rebased to the firstmatch to account for any offsets, and combined with the actual matchtext to generate a format hash key.

By including the rebased coordinates in a quote sent for inspectionalong with the format hash key, any systematic misparsing requiringrecategorization or editing of the quote during validation can beautomate after the first intervention by applying the changes made toall future instances.

These restrictions of confidentiality do not apply to all participantsin the market. For example, hedge funds that outsource their middle andback office functions (risk management) could reasonably be expected toforward any markets they are shown to their risk managers to verify thatthe books are being marked correctly. In this scenario, the system couldbe configured slightly differently, with one central parser, processingdata from a number of clients as in FIG. 3.

In another embodiment, originators of the market data employ themethods, software, and/or hardware of the invention to either preformatemail, or to create quotes for distribution to clients as in FIG. 5.

In another embodiment, a parser is located within a commoncommunication/messaging network, such that quotes are distributed alongwith—or instead of—the original text from which they were derived as inFIG. 6.

In another embodiment, a system is configured so that each user sharesthe maintenance of the system, with updates being shared between peersas in FIG. 4.

In another embodiment, for markets with well structured/consistent datasources, no central maintenance and verification may be desired. In thisconfiguration (illustrated by example in FIG. 7), the system could bemaintained by clients, and through periodic software updates.

FIG. 8 illustrates a process of the invention wherein source data, whichcan comprise data in any format, is stored on a computer readable medium(CRM), processed by, for example, parsing, then stored again, andcompared to at least one pre-selected criterion.

FIG. 9 illustrates a similar process, but with identification andverification of suspect data. In the embodiment shown, verification isachieved through transmission of hashed suspect source data. In otherembodiments, such as, for example, where the methods, software, andhardware of the invention are practiced on a local network, transmissionmay not be necessary. Although not shown, the transmitted data can beencrypted. Following display of price quotes or verified price quotes,the user preferably selects the best price for an over-the-countersecurity and places an order to the originator of the best price.

FIG. 10 illustrates a process of the invention that shows how hashingcan be used in at least one embodiment in generating verified pricequotes. In the embodiment illustrated, suspect data is hashed, and aresulting hash key is encrypted. In general, however, encryption of thehash key is not required. Following display of price quotes or verifiedprice quotes, the user preferably selects the best price for anover-the-counter security and places an order to the originator of thebest price. At any suitable step in the process, data can be stored on acomputer readable medium.

FIG. 11 illustrates an embodiment where data comprising suspect quotesfor an over-the-counter security are hashed, the hash keys areencrypted, transmitted to, for example, a remote hub or location, thehash keys decrypted and the quotes verified, the verified quotesre-hashed and transmitted back, and then the hash keys decrypted andverified price quotes extracted. Storage onto a computer readablemedium, and display of the data, is not indicated in the processdiagram. However, the suspect quotes, hashed data, encrypted keys, andthe like can be conveniently stored on a suitable computer readablemedium at any convenient step in the process. The verified quotes arepreferably displayed to a user on a display such as a computer terminal,and preferably ranked according to price. The user can then select thebest price and place an order according to the displayed verified pricequotes.

Advantages of the invention include the ability to determine best marketprices in real time and track price histories for over-the-countersecurities, thus enabling users to price portfolios using verifiedmarket prices in real time. The invention also provides the ability tostore verified price data and manipulate it in any suitable manner suchas, for example, commercial spreadsheet applications.

The capability of pricing a portfolio in real time with verified pricequote data provides a significant advantage to users, and in particularto risk managers. Because the invention provides verified price quotedata in over-the-counter markets, the invention allows users to applymore accurate data to mathematical models of risk assessment.Accordingly, users can better manage portfolios by improved estimationof market risks in over-the-counter markets. A nonlimiting example of amathematical approach to risk assessment that can benefit from theinvention includes statistical measures of risk exposure that generateprobabilistic statements. For example, users can use the invention toimprove the process of determining Value-at-Risk (VaR) by providing notonly accurate historical price data, but verified real time price quotesthat can be used to provide an accurate, verified current portfolioposition.

Accordingly, the invention also comprises a method for computing VaR,comprising employing the methods of the invention to generate real timeprice quotes, including verified price quotes, and using the real timeprice quotes in a VaR method. Any suitable VaR model or algorithm can beused in connection with the invention. In some embodiments, theinvention comprises employing the methods of the invention to generateverified price quotes and using the verified price quotes to compute aVaR for a portfolio, wherein the VaR is employed to set trading limitson the securities comprising the portfolio.

EXAMPLES

The following examples are intended to explain the invention further.

Reducing Misclassifications

The idea behind the use of a format hash key within the invention is tosignificantly reduce the amount of recurring misclassifications by theparser. By creating a unique format identifier, and storing down anyreclassification that has to be done by the data editing team, it ispossible to prevent or at least automate the handling of furtheroccurrences.

An algorithm creates a hash key from all matches made by the parser,with the exception of any relating to the actual level of quotes, asthese will always be changing. By creating a hash key using these actualmatches, and their rebased coordinates within the text, it is possibleto uniquely identify formats. In one embodiment, the rebase ofcoordinates is done onto the first included match.

Consider the example emails below. Both generate the same hash key, andwhen combined with the rebased coordinate of the actual quote matchuniquely identify the instance of a quote. RHODIA CURVE UPDATE - 5 bpswider today (results in line + general softer market tone as evidence byequity) 1y 160/210 2y 365/415 3y 455/465 5y 515/530 7y 535/555 10y 555/580 5 m × 5 m RHODIA CURVE 1y 155/205 2y 360/410 3y 450/460 5y510/525 7y 530/550 10y  550/

Hash key:

RHODIA(0,0)1Y(1,2)2Y(1,3)3Y(1,4)5Y(1,5)7Y(1,6)10Y(0,7)

Encrypted Hash key:

2zi+EFLV9kx/t/+o8S/i+g==

Using Hash Keys in the Credit Default Swap Market

In one example of a CDS application of the invention, the HashKey willidentify a CDS quote and have the qualities of uniqueness and encryptionas described below. Here, the HashKey is especially not intended as acompressed-data mechanism for decryption at a central hub, furtherdescribed below.

HashKey Uniqueness

A CDS quote scraped by a suitable parser comprises two sets ofproperties, those relating to the underlying email and those relating tothe quote itself. Properties of the underlying email are not conduciveto identifying quote uniqueness. If a trader were to send the same quotewithin multiple emails a short time apart, the inclusion of emailspecific properties within the HashKey would invalidate the quotes'uniqueness. EMAIL PROPERTY REASON FOR NOT INCLUDING IN HASHKEY emailIdNot unique per client. recFrom Resolves to a traders Bloomberg a/c - notthe email originator. sentTo Different client recipients. sent Differingforward timestamps from each Bloomberg mailbox. body Contains non-uniqueembedded forward info.

Client database Emails table. Properties of a scraped CDS quote are bydefinition ideal for defining uniqueness. CDS QUOTE INCLUDE IN PROPERTYHASHKEY COMMENT quoteId No Not unique per client. entityId Yes bid Yesoffer Yes upfBid Yes upf = upfront. upfOffer Yes upf = upfront.isTradedQuote No Very rarely differs between quotes. term Yes termDateYes dealTypeId Yes currencyId Yes bidSize No Very rarely differs betweenquotes. offerSize No Very rarely differs between quotes. sourceId YesSee ¹ below. quoteDate Yes quoteTime Yes See ² below. emailId No Notunique per client. active No Status changes during a quotes lifetime.UserId No Not unique per client. LastAction No Not unique per client.

Client database CdsQuotes table. CDS QUOTE INCLUDE IN PROPERTY HASHKEYCOMMENT contextStart No First character of the quotes' context withinthe Emails table body field. See ³ below. contextFinish No Lastcharacter of the quotes' context within the Emails table body field. See³ below. hashKey No¹ The sourceId contributes a sizeable weight to a CDS quotes'uniqueness, therefore, it is preferable to include. RS confirms thatprovided the HashKey is not decrypted at [INSERT WHERE DECRYPTED; ALLEMBODIMENTS, I.E., LOCAL VS CENTRAL] hashkey does not get decrypted# anywhere. Is it purely used to identify uniqueness anonymously. or FDECentral then it is fine to use.² In this example, the quoteTime is imperative for Data Editingpurposes. It is the receipt time of the underlying email. A variation ofonly 1 second will invalidate a quotes' uniqueness. Therefore, forinclusion in the HashKey the quote time will be floored to three20-minute# segments per hour. For example, quotes arriving between 10:00AM and10:19AM will all be timed as 10:00AM, those arriving between 10:20AM and10:39AM as 10:20AM, etc. An exercise will be undertaken to determine theoptimum number of time intervals per day or hour. A SQL join between theEmails # and CdsQuotes tables will return the actual context for thequote, to be included in the HashKey.

HashKey Encryption

Once constructed the HashKey needs to be both encrypted and obfuscated.MD5 encryption is applied to the aggregated HashKey. The result is castto a C# string/SQL char(16) (128 bits=16 bytes) for developerconvenience (TBC). MD5 was developed by Professor Ronald L. Rivest ofMIT. What it does, to quote the executive summary of rfc1321, is: TheMD5 algorithm takes as input a message of arbitrary length and producesas output a 128-bit “fingerprint” or “message digest” of the input. Itis conjectured that it is computationally infeasible to produce twomessages having the same message digest, or to produce any messagehaving a given pre-specified target message digest. The MD5 algorithm isintended for digital signature applications, where a large file must be“compressed” in a secure manner before being encrypted.

HashKey Algorithm

HashKey=sourceId+entityId+bid+offer+upfBid+upfOffer+term+termDate+dealTypeId+currencyId+quoteDate+quoteTime+context

Verified/Reclassified data is returned to clients with the sameidentifying hashkey.

While the invention has been described in connection with specificembodiments thereof, it will be understood that it is capable of furthermodifications and this application is intended to cover any variations,uses, or adaptations of the invention following, in general, theprinciples of the invention and including such departure from thepresent disclosure as come within known or customary practice within theart to which the invention pertains and as may be applied to theessential features hereinbefore set forth and as follows in the scope ofthe appended claims.

1. A method for providing a price quote on a security traded in anover-the-counter financial market, comprising: (a) receiving source datacomprising price information of the security; (b) storing the sourcedata on a computer readable medium; (c) processing the source data usinga computer processor, wherein the processing comprises extracting aprice quote from the source data, comparing the price quote to at leastone pre-selected criterion, and storing the compared price quote on acomputer readable medium; and, (d) displaying the compared price quote,wherein the compared price quote comprises a price quote for a securitytraded in an over-the-counter financial market.
 2. A method according toclaim 1, wherein the source data is received from multiple sources andcomprises more than one price quote for the security.
 3. A methodaccording to claim 2, wherein the source data received from at least afirst source and a second source, wherein the source data received fromthe first source is in a different format than the source data receivedfrom the second source.
 4. A method according to claim 2, wherein theformat of the source data comprises an email, html, text, xml, orcombinations thereof.
 5. A method according to claim 1, wherein the stepof processing the source data comprises parsing the source data beforecomparing the source data to the at least one pre-selected criterion. 6.A method according to claim 4, wherein the parsing comprisescategorizing words, patterns, and/or numbers in the data source toidentify market data in the source data.
 7. A method according to claim1, further comprising designating source data that does not meet the atleast one criterion as suspect data.
 8. A method for generating verifiedprice quotes for securities traded in an over-the-counter financialmarket, comprising: (a) receiving source data on a first computerreadable medium, wherein the source data comprises information about theprice of a security; (b) storing the source data on the computerreadable medium; (c) processing the source data, wherein the processingcomprises identifying suspect source data, assigning a hash key tosuspect source data, wherein the hash key comprises a price quote andthe identity of the data source; (d) verifying the suspect source datausing the hash key, and (e) displaying information about the verifiedsuspect source data to a user.
 9. A method according to claim 8, whereinthe format of the source data comprises an email, html, text, xml, orcombinations thereof.
 10. A method according to claim 8, wherein thestep of processing the source data further comprises parsing the sourcedata.
 11. A method according to claim 10, wherein the step of processingfurther comprises comparing the source data to at least one pre-selectedcriterion.
 12. A method according to claim 10, wherein the parsingcomprises categorizing words, patterns, and/or numbers in the datasource to identify market data in the source data.
 13. A methodaccording to claim 8, wherein the hash key comprises data from two ormore suspect sources.
 14. A method according to claim 8, wherein thehash key is encrypted.
 15. A method according to claim 8, wherein thestep of verifying the suspect source data using the hash key comprisestransmitting the suspect source data in the hash key to a verifier,wherein the verifier verifies the suspect source data and transmits to auser a computer readable message comprising a verification, averification failure, or a combination thereof.
 16. A method accordingto claim 14, wherein the verification includes a price quote for asecurity.